Code underlying the publication: A Benchmark for the Application of Distributed Control Techniques to the Electricity Network of the European Economic Area

doi: 10.4121/d2c0d075-1c49-41af-8113-5e50c27ca97e.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/d2c0d075-1c49-41af-8113-5e50c27ca97e
Datacite citation style:
Riccardi, Alessandro; Laurenti , Luca; De Schutter, Bart (2024): Code underlying the publication: A Benchmark for the Application of Distributed Control Techniques to the Electricity Network of the European Economic Area. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/d2c0d075-1c49-41af-8113-5e50c27ca97e.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software

The European Economic Area Electricity Network Benchmark (EEA-ENB) is a multi-area power system representing the European network of transmission systems for electricity to facilitate the application of distributed control techniques. In the EEA-ENB we consider the Load Frequency Control (LFC) problem in the presence of renewable energy sources (RESs), and energy storage systems (ESSs). RESs are known to cause instability in power networks due to their inertia-less and intermittent characteristics, while ESSs are introduced as a resource to mitigate the problem. In the EEA-ENB, particular attention is dedicated to Distributed Model Predictive Control (DMPC), whose application is often limited to small and homogeneous test cases due to the lack of standardized large-scale scenarios for testing, and due to the large computation time required to obtain a centralized MPC action for performance comparison with DMPC strategies under consideration. The second problem is exacerbated when the scale of the system grows. To address these challenges and to provide a real-world-based and control-independent benchmark, the EEA-ENB has been developed. The benchmark includes a centralized MPC strategy providing performance and computation time metrics to compare distributed control within a repeatable and realistic simulation environment.

history
  • 2024-03-27 first online, published, posted
publisher
4TU.ResearchData
funding
  • CLariNet (grant code 101018826) [more info...] European Research Council
organizations
TU Delft, Faculty of Mechanical Engineering, Delft Center for Systems and Control

DATA

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/78170934-ebb2-4774-9cf9-ec584ad088a0.git